Learn embeddings, similarity search, HNSW, IVF, semantic search, RAG, and recommender systems with hands-on examples.
What you will learn
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Explain what embeddings are and how they enable similarity search.
Learn how to choose and fine-tune embedding models for custom applications.
Learn how vector databases work in terms of indexing & retrieval.
Familiarize yourself with the vector database landscape and different applications.
English
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